Ni2+对好氧颗粒污泥系统性能的影响

以城镇污水处理厂A²/O工艺的回流污泥作为接种污泥,在序批式反应器（SBR）中培养好氧颗粒污泥（AGS）,探究Ni²⁺对AGS系统的影响.结果表明：在25℃的条件下,50d左右培养出成熟的AGS,其形态多呈球状或椭球状,外表分布着少量丝状菌,颗粒污泥粒径主要在2~4mm,MLSS达6000mg/L,SVI维持在40~50mL/g.将Ni²⁺作用于培养出的成熟AGS,Ni²⁺在0~2mg/L的浓度范围内会提高AGS的稳定性,使MLSS上升,SVI降低;同时会促进AGS分泌胞外多聚物（EPS）,EPS组成成分中的蛋白质（PN）明显多于多糖（PS）;Ni²⁺对好氧颗粒污泥去除总氮（TN）的抑制程度要大于COD,最终COD去除率可维持在95%以上,TN去除率可维持在70%以上.     

基于铁锰泥的除砷吸附剂性能比较及吸附机理

为解决反冲洗铁锰泥粉末吸附剂（BSPA）使用后难以泥水分离问题,将除铁锰水厂生物滤池产生的反冲洗泥制成颗粒吸附剂（GA）和磁性粉末吸附剂（MPA）,并对BSPA、GA和MPA的除砷性能进行了比较,通过SEM、TED、XRD、BET、FTIR等技术对3种材料进行了表征,寻找3种吸附剂之间除砷性能差异的根源.结果表明,BSPA、GA和MPA对As （V）的最大吸附容量分别为40.980,5.048,8.694mg/g,改性后的吸附材料GA和MPA对砷的吸附能力下降.BSPA是一种以纤铁矿为主的无定形结构混合物,并混有针铁矿和结晶度差的水铁矿,GA的XRD图谱中出现石英晶体和少量赤铁矿晶体的衍射峰,而MPA的主要成分为结晶程度较高的磁赤铁矿.3种材料中均存在有利于吸附的含羟基官能团.BSPA、MPA和GA的比表面积分别为253.150,238.660,43.803m²/g.物相改变且结晶程度增加、表面羟基减少和比表面积降低是导致GA和MPA的砷吸附容量比BSPA低的主要因素.     

颗粒物分界层Mie散射激光雷达识别的sigmoid算法

基于成都市2013年6月~2015年5月期间由Mie散射激光雷达探测的大气消光系数廓线资料,发现混合层以上在颗粒物消光和分子消光之间一致存在一个S型的过渡区,利用sigmoid函数对此分布形态进行模拟,通过计算该函数上下曲率最大点所在的高度,据此提出了颗粒物分界层Mie散射激光雷达识别的sigmoid算法.针对该算法模拟效果的分析表明,颗粒物分界层过渡区附近大气消光系数理论廓线和实测廓线保持了高度的相关性,二者在春夏秋冬四季的相关系数（R）分别为0.9971±0.0052、0.9935±0.0167、0.9979±0.0038和0.9990±0.0021（均通过α=0.05的显著性检验）.基于sigmoid算法计算的颗粒物分界层过渡区与成都市温江站探空资料得到的逆温层之间存在很好的对应关系.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

大气颗粒物中元素碳的直接测定

对原来用元素分析仪测定大气颗粒物样品中有机碳、元素碳的方法[1 ] 进行改进 ,将差减法间接测定元素碳改为一步直接测定元素碳。有机碳、元素碳的测量标准偏差的平均值分别为 0 35 %、0 34% ,提高了元素碳的测量精度 ,同时避免了误差传递 ,解决了差减法测定元素碳时出现负值的情况。     

The collection of PM10 for toxicological investigation: comparisons between different collecting devices

A positive correlation has been established between increased levels of airborne particulate pollution and adverse health effects, the toxicological mechanisms of which are poorly understood. For toxicologists to unambiguously determine thesemechanisms, truly representative samples of ambient PM₁₀ are required. This presents problems, as PM₁₀ collecting equipment commonly employed, such as the Tapered Element Oscillating Microbalance (TEOM®), heat the inflow toexclude moisture or use fibrous filters, resulting in a PM₁₀sample that may have undergone significant chemical change on thefilter surface or is contaminated by filter fibres. Other systems(i.e. Negretti and Partisol) can successfully collect PM₁₀ without chemical alteration or filter contamination. Comparativecollections from Port Talbot, S. Wales suggest that TEOMs and Negretti/Partisol systems collect different PM₁₀'s; the principle difference arising from the TEOM's heating chamber, which precipitates water-soluble ions and volatilises some organic components. This results in both the mass and compositionof the PM₁₀'s being altered. Particle size distributionsfor Negretti and Partisol collections highlighted differences mainly attributed to different flow rates. The results of thiswork demonstrate that simple correlations between PM₁₀ massand adverse health effects are problematic. Furthermore, elucidation of the complex fractionation and chemical changes indifferent collectors is necessary.     

NBIAS中污泥龄对脱氮除磷效果的影响

探讨无回流间歇曝气系统 (简称 NBIAS) ,处理城市污水的污泥龄 ( SRT)对脱氮除磷及有机物去除效果的影响。通过原污水流程试验和人工合成污水静态模拟实验 ,试验结果表明 :在水温为 2 0℃～ 30℃ ,污泥负荷为 0 .2 5～0 .45kg CODcr/ kg MLSS· d,SRT为 1 8～ 2 2 d,HRT为 8～ 1 0 h时 ,利用原污水作为碳源 ,NBIAS在保持较高的 CODcr去除率的同时 ,总氮和总磷的去除率均在 80 %以上。     

Removal of high concentrated ammonia nitrogen from landfill leachate by landfilled waste layer

The landfill of municipal solid waste(MSW) could be regarded as denitrification reactor and involved in ammonia nitrogen biological removal process. In this research, the process was applied to municipal solid waste collected in Shanghai, China, which was characterized by high food waste content. The NH4^ removal efficiency in the system of SBR nitrifying reactor followed by fresh and matured landfilled waste layer in series was studied. In the nitrifying reactor, above 90% of NH4^ in leachate was oxidized to NO2^- and NO3^- . Then high concentrated NO2^- and NO3^- were removed in the way of denitrification process in fresh landfilled waste layer. At the same time, degradation of fresh landfilled waste was accelerated. Up to the day 120, 136.5 gC/(kg dry waste) and 17.9 gN/(kg dry waste) were converted from waste layer. It accounted for 50.15 % and 86.89 % of the total carbon and nitrogen content of preliminary fresh waste, which was 4.42 times and 5.17 times higher than that of reference column respectively. After filtering through matured landfilled waste, BOD5 concentration in leachate dropped to below 100 mg/L, which would not affect following nitrification adversely. Because the matured landfilled waste acted as a well methanogenic reactor, 23% of carbon produced accumulatively from fresh landfilled waste degradation was converted into CH4.     

浅议影响污水生物除磷的因素

针对目前水体富营养化严重，污水除磷要求高的现状，着重分析阐述了在目前条件下的对污水生物除磷产生较显著影响的因素，如，溶解氧及氧化还原电位，硝酸盐，泥龄，进水营养比等，以期对生产实践有所帮助。     

废水反硝化除氮

反硝化是ＮＯ３＾－在反硝化细菌作用下，经ＮＯ２＾－、ＮＯ、Ｎ２Ｏ被还原为Ｎ２。反硝化对ＮＯ３＾－及有机基质呈零级动力学反应。文章还介绍了生物反硝化的生化反应，反硝化细菌以及基质、温度、溶解氧、ＰＨ对反硝化作用的影响。